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Chronic Obstructive Pulmonary Disease (COPD) Diagnosis using Electromyography (EMG)
- 1st Edition - January 16, 2022
- Authors: Archana Bajirao Kanwade, Vinayak Bairagi
- Language: English
- Paperback ISBN:9 7 8 - 0 - 3 2 3 - 9 0 0 5 0 - 8
- eBook ISBN:9 7 8 - 0 - 3 2 3 - 8 8 6 0 8 - 6
Chronic Obstructive Pulmonary Disease (COPD) Diagnosis using Electromyography (EMG) presents a new and innovative method of COPD diagnosis using EMG to analyze sternomas… Read more
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Request a sales quoteChronic Obstructive Pulmonary Disease (COPD) Diagnosis using Electromyography (EMG) presents a new and innovative method of COPD diagnosis using EMG to analyze sternomastoid muscle activity using features extraction and classification. The book describes the methodology of EMG analysis, the slope-based onset detection algorithm and SEMG analysis in time, frequency and time frequency domain analyses. It also explores the identification of frequencies for single frequency Continuous Wavelet Transform (CWT) analysis and feature extraction and selection for successful classification COPD into its severity grades.
The book provides a compilation of all techniques used in the literatures and emphasizes newly proposed techniques for the early detection of COPD. Fully comprehensive, the book includes discussion of limitations of existing methods for COPD diagnosis and introduces new efficient methods for COPD identification, classification and early diagnosis.
- Provides an easy, simple and comprehensive guide to using EMG analysis for COPD diagnosis
- Presents detailed explanations of the recently developed slope-based onset detection algorithm for muscle activity detection, along with numerous original figures, tables and graphs to aid interpretation
- Includes a complete review of various features, such as extraction using single frequency CWT analysis and the feature selection algorithm for COPD diagnosis
Researchers, academics and scientists working in the field of Respiratory diseases, Biomedical Engineering, EMG signal processing and Pulmonologists. Biomedical Signal Processing Course specifically for the EMG signal Processing details. Respiratory medicine branch for Chronic Obstructive Pulmonary Disease subject
- Cover image
- Title page
- Table of Contents
- Copyright
- About the author
- Preface
- Acknowledgments
- Chapter 1. Introduction
- Abstract
- 1.1 Chronic Obstructive Pulmonary Disease (COPD)
- 1.2 Chronic Obstructive Pulmonary Disease burden
- 1.3 Current techniques for assessing chronic obstructive pulmonary disease
- 1.4 Respiratory muscles and mechanics of respiration
- 1.5 Role of sternomastoid muscle in chronic obstructive pulmonary disease
- 1.6 Electromyography
- 1.7 Need for research
- 1.8 Summary
- References
- Chapter 2. Methodology
- Abstract
- 2.1 Introduction
- 2.2 Methodology
- 2.3 Recording techniques
- 2.4 Skin preparations
- 2.5 Electromyography affecting factors
- 2.6 Electromyography filtering and associated noise
- 2.7 Electromyography analysis
- 2.8 Feature selection and classification
- 2.9 Summary
- References
- Chapter 3. Chronic Obstructive Pulmonary Disease and healthy classification
- Abstract
- 3.1 Introduction
- 3.2 System information
- 3.3 Time domain analysis
- 3.4 Onset detection algorithm
- 3.5 Feature selection
- 3.6 Classification algorithm
- 3.7 Results
- 3.8 Summary
- References
- Chapter 4. Chronic Obstructive Pulmonary Disease grade classification
- Abstract
- 4.1 Introduction
- 4.2 Frequency domain analysis
- 4.3 Time-frequency domain analysis
- 4.4 Feature selection algorithm
- 4.5 Classification of Chronic Obstructive Pulmonary Disease grades
- 4.6 Results
- 4.7 Summary
- References
- Chapter 5. Early detection of Chronic Obstructive Pulmonary Disease
- Abstract
- 5.1 Introduction
- 5.2 Literature survey
- 5.3 Early diagnosis model
- 5.4 Early COPD diagnosis results
- 5.5 Summary
- References
- Chapter 6. Future scope and application
- Abstract
- 6.1 Conclusion
- 6.2 Future scope and applications
- Index
- No. of pages: 192
- Language: English
- Edition: 1
- Published: January 16, 2022
- Imprint: Academic Press
- Paperback ISBN: 9780323900508
- eBook ISBN: 9780323886086
AK
Archana Bajirao Kanwade
Dr. Archana Bajirao Kanwade has completed M.E. in Electronic-Communication in 2009 from Shivaji University. University of Pune has awarded her a PhD degree in Electronics and Telecommunication Engineering in 2020. She has 17 years of teaching experience and 09 years of research experience. She has filed a patent on COPD diagnosis using EMG analysis. She has published more than 35 technical papers, out of which 28 papers are in International journals. She has 4 papers indexed in Scopus Journals and 2 papers in SCI indexed journals. She is reviewer for three Scientific Journals.
She has also been invited as resources person for invited talk. She is a member of IEEE SIGHT. Currently she is associated with Sinhgad Institute of Technology and Science, (Affiliated college to S P Pune University), India as Assistant Professor in Electronics and Telecommunication Engineering. She is recognized PG Guide in Electronics and Telecommunication Engineering of Savitribai Phule Pune University.
Affiliations and expertise
Assistant Professor, Department of E&TC, Sinhgad Institute of Technology and Science, Narhe , SPPU, Pune, IndiaVB
Vinayak Bairagi
Dr. Vinayak K. Bairagi, is a recognized PhD guide in Savitribai Phule Pune University. He is working as Professor at Department of E electronics and Telecommunication Engg. and actively working as Chairman, IEEE Signal Processing Society Pune Chapter. He has teaching experience of 14 years and research experience of 10 years. He has filed 12 patents and 5 copyrights in technical field. He has published more than 70 papers. He has received IEI national level Young Engineer Award (2014) and ISTE national level Young Researcher Award (2015) for his excellence in the field of engineering. He also has 5 books and 6 book chapters on his credits. His area of interest is Biomedical Signal Processing and Brain Imaging.
Affiliations and expertise
PhD Mentor in Electronics Engineering, Savitribai Phule Pune University, Pune, Maharashtra, India